Method and apparatus for entropy-coding/entropy-decoding video data using different binarization methods

ABSTRACT

Provided are a method and apparatus for entropy-encoding/entropy-decoding video data. The method of entropy-encoding video data includes binarizing coefficients of the frequency domain, which are generated by transforming a residual block of a current block into the frequency domain, using different binarization methods and performing binary arithmetic coding on the binarized coefficients. In this way, the coefficients are binarized adaptively according to whether the frequencies of the coefficients are high or low, thereby improving the compression efficiency of the video data.

CROSS-REFERENCE TO RELATED PATENT APPLICATION

This application is a Continuation of U.S. application Ser. No.12/108,697 filed Apr. 24, 2008 in the United States Patent and TrademarkOffice, which claims priority from Korean Patent Application No.10-2007-0058579, filed on Jun. 14, 2007, in the Korean IntellectualProperty Office, the disclosure of which is incorporated herein in itsentirety by reference.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention generally relates to a method and apparatus forentropy-coding/entropy-decoding video data, and more particularly, to amethod and apparatus for entropy-coding/entropy-decoding video data byefficiently binarizing discrete cosine transform (DCT) coefficients of aresidual block of a current block.

2. Description of the Related Art

In video compression standards, such as moving picture expert group(MPEG)-1, MPEG-2, and H.264/MPEG-4 advanced video coding (AVC), apicture is divided into predetermined units of video processing, e.g.,macroblocks, for video encoding. Each of the macroblocks is then encodedusing interprediction or intraprediction. Next, an optimal encoding modeis selected based on the size of data of the encoded macroblock and thedegree of distortion between the encoded macroblock and the originalmacroblock and the macroblock is encoded in the selected encoding mode,as will now be described in detail with reference to FIG. 1.

FIG. 1 is a block diagram of a video encoder 100 according to therelated art.

Referring to FIG. 1, a motion compensation unit 104 or anintraprediction unit 106 performs interprediction or intraprediction inblock units. The motion compensation unit 104 performs interpredictionon the current block based on a motion vector of the current block thatis estimated by a motion estimation unit 102, by searching for areference picture stored in a frame memory 120. The intraprediction unit106 performs intraprediction on the current block using pixels includedin a previously encoded region of the current picture.

A prediction block that is a prediction value for the current blockgenerated as a prediction result is subtracted from the original block,thereby generating a residual block. The generated residual block istransformed into the frequency domain by a transformation unit 108. Thetransformation unit 108 also performs discrete cosine transformation(DCT), thereby generating coefficients in the frequency domain for theresidual block, i.e., DCT coefficients. A quantization unit 110quantizes the DCT coefficients. The quantized coefficients areentropy-coded by an entropy-coding unit 112 and then inserted into abitstream.

The coefficients quantized by the quantization unit 110 are inverselyquantized by an inverse quantization unit 114 and an inversetransformation unit 116 performs inverse discrete cosine transformation(IDCT) on the inversely quantized coefficients. The residual blockreconstructed by the IDCT is added to the prediction block, therebyreconstructing the original block.

The reconstructed original block is deblocking-filtered by a filteringunit 118 and then stored in the frame memory 120 in order to be used forinterprediction or intraprediction of another block.

In H.264/AVC coding, entropy-coding is performed by usingcontext-adaptive variable length coding (CAVLC) or context-adaptivebinary arithmetic coding (CABAC). Entropy-coding is performed byapplying different entropy-coding methods to different syntax elements.

Among a variety of syntax elements, DCT coefficients are CAVLC-coded byrun-level coding. A DCT coefficient having a value of ‘0’ is called a‘run’ and DCT coefficients having values other than ‘0’ are called a‘level’. The DCT coefficients are binarized separately for ‘runs’ and‘levels’ and bin strings generated by the binarization arearithmetically coded using a context model.

The DCT coefficients having values other than ‘0’, i.e., the levels, arebinarized into variable-length codes using concatenated unary/k^(th)order exponential Golomb binarization and then bin strings generated bythe binarization are arithmetically coded, as will now be described indetail with reference to FIG. 2.

Referring to FIG. 2, levels are binarized using a binarization methodthat is a combination of truncated unary binarization having a maximumcode value (cMax) of ‘14’ and 0th order exponential Golomb binarization.

A level having a value (abs_level)<=14 is binarized using only truncatedunary binarization and a level having a value >14 is binarized using acombination of truncated unary binarization and exponential Golombbinarization.

However, in the probability distribution of DCT coefficients, levels areconcentrated in coefficients of a low-frequency component and runs areconcentrated in coefficients of a high-frequency component. In otherwords, levels are concentrated in an upper left portion of a DCTcoefficient block generated by performing DCT on a residual block andruns are concentrated in a lower right portion of the DCT coefficientblock. Therefore, it is inefficient to apply the same binarizationmethod as illustrated in FIG. 2 to DCT coefficients because the DCTcoefficients are binarized without consideration of the probabilitydistribution of runs and levels.

SUMMARY OF THE INVENTION

The present invention provides a method and apparatus for efficientlyentropy-coding/entropy-decoding video data by considering theprobability distribution of discrete cosine transform (DCT)coefficients, and a computer-readable recording medium having recordedthereon a program for executing the method.

According to one aspect of the present invention, there is provided amethod of entropy-coding video data. The method includes binarizingcoefficients of a frequency domain, which are generated by transforminga residual block of a current block into the frequency domain, usingdifferent binarization methods and performing binary arithmetic codingon the binarized coefficients.

The coefficients of the frequency domain may be discrete cosinetransformation (DCT) coefficients generated by performing DCT on theresidual block.

The binarization of the coefficients may include grouping the DCTcoefficients generated by performing the DCT into a plurality of groupsbased on whether frequencies of the DCT coefficients are high or low andbinarizing the DCT coefficients by applying different binarizationmethods to the plurality of groups.

The binarization of the coefficients may include binarizing the DCTcoefficients using different concatenated unary/k^(th) order exponentialGolomb binarization method based on whether the frequencies of the DCTcoefficients are high or low.

According to another aspect of the present invention, there is provideda video encoding method including generating a prediction block that isa prediction value for a current block and subtracting the generatedprediction block from the current block, thereby generating a residualblock of the current block, generating discrete cosine transformation(DCT) coefficients for the residual block by performing DCT on thegenerated residual block and quantizing the generated DCT coefficients,and grouping the quantized DCT coefficients into a plurality of groupsbased on whether frequencies of the DCT coefficients are high or low,binarizing the DCT coefficients by applying different binarizationmethods to the plurality of groups, and performing binary arithmeticcoding on the binarized coefficients.

According to another aspect of the present invention, there is providedan apparatus for entropy-coding video data. The apparatus includes abinarization unit that binarizes coefficients of a frequency domain,which are generated by transforming a residual block of a current blockinto the frequency domain, using different binarization methods and abinary arithmetic coding unit that performs binary arithmetic coding onthe binarized coefficients.

According to another aspect of the present invention, there is provideda video encoding apparatus including a residue generation unit, atransformation unit, a quantization unit, and an entropy-coding unit.The residue generation unit generates a prediction block that is aprediction value for a current block and subtracts the generatedprediction block from the current block, thereby generating a residualblock of the current block. The transformation unit generates discretecosine transformation (DCT) coefficients for the residual block byperforming DCT on the generated residual block. The quantization unitquantizes the generated DCT coefficients. The entropy-coding unit groupsthe quantized DCT coefficients into a plurality of groups based onwhether frequencies of the DCT coefficients are high or low, binarizesthe DCT coefficients by applying different binarization methods to theplurality of groups, and performs binary arithmetic coding on thebinarized coefficients.

According to another aspect of the present invention, there is provideda method of entropy-decoding video data. The method includes receivingdata regarding a residual block which is generated by binarizingcoefficients of a frequency domain generated by transforming theresidual block of a current block into a frequency domain by usingdifferent binarization methods and then performing binary arithmeticcoding on the binarized coefficients and performing binary arithmeticdecoding on the received data, thereby generating the binarizedcoefficients, and inversely binarizing the binarized coefficients usingdifferent inverse binarization methods.

According to another aspect of the present invention, there is provideda video decoding method including generating binarized discrete cosinetransformation (DCT) coefficients by performing binary arithmeticdecoding on data regarding a residual block which is generated byperforming entropy-coding on the residual block of a current block,grouping the binarized DCT coefficients into a plurality of groups basedon whether frequencies of the DCT coefficients are high or low, andinversely binarizing the DCT coefficients by applying different inversebinarization methods to the plurality of groups, performing inversequantization on the inversely binarized DCT coefficients and performinginverse DCT on the inversely quantized DCT coefficients, therebyreconstructing the residual block, and generating a prediction blockthat is a prediction value for the current block and adding thegenerated prediction block to the reconstructed residual block, therebyreconstructing the current block.

According to another aspect of the present invention, there is providedan apparatus for entropy-decoding video data, including an arithmeticdecoding unit and an inverse binarization unit. The arithmetic decodingunit receives data regarding a residual block which is generated bybinarizing coefficients of a frequency domain generated by transformingthe residual block of a current block into a frequency domain usingdifferent binarization methods and then performing binary arithmeticcoding on the binarized coefficients and performs binary arithmeticdecoding on the received data, thereby generating the binarizedcoefficients. The inverse binarization unit inversely binarizes thebinarized coefficients using different inverse binarization methods.

According to another aspect of the present invention, there is provideda video decoding apparatus including an entropy-decoding unit, aninverse quantization unit, an inverse transformation unit, and areconstruction unit. The entropy-decoding unit generates binarizeddiscrete cosine transformation (DCT) coefficients by performing binaryarithmetic decoding on data regarding a residual block which isgenerated by performing entropy-coding on the residual block of acurrent block, and groups the binarized DCT coefficients into aplurality of groups based on whether frequencies of the binarized DCTcoefficients are high or low, and inversely binarizes the DCTcoefficients by applying different inverse binarization methods to theplurality of groups. The inverse quantization unit performs inversequantization on the inversely quantized DCT coefficients. The inversetransformation unit performs inverse DCT on the inversely quantized DCTcoefficients, thereby reconstructing the residual block. Thereconstruction unit generates a prediction block that is a predictionvalue for the current block and adds the generated prediction block tothe reconstructed residual block, thereby reconstructing the currentblock.

According to another aspect of the present invention, there is provideda computer-readable recording medium having recorded thereon a programfor executing the method of entropy-encoding video data, the method ofentropy-decoding video data, the video encoding method, and the videodecoding method.

BRIEF DESCRIPTION OF THE DRAWINGS

The above and other features and advantages of the present inventionwill become more apparent by describing in detail exemplary embodimentsthereof with reference to the attached drawings in which:

FIG. 1 is a block diagram of a video encoder according to the relatedart;

FIG. 2 illustrates a method for binarizing coefficients of a frequencydomain according to the related art;

FIG. 3 is a block diagram of a video encoder according to an exemplaryembodiment of the present invention;

FIG. 4 is a block diagram of an entropy-coding unit according to anexemplary embodiment of the present invention;

FIG. 5 illustrates grouping of DCT coefficients according to anexemplary embodiment of the present invention;

FIG. 6 is a table illustrating binarization of DCT coefficientsaccording to an exemplary embodiment of the present invention;

FIG. 7 is a table illustrating binarization of DCT coefficientsaccording to another exemplary embodiment of the present invention;

FIG. 8 is a flowchart illustrating a method of entropy-coding video dataaccording to an exemplary embodiment of the present invention;

FIG. 9 is a block diagram of a video decoder according to an exemplaryembodiment of the present invention;

FIG. 10 is a block diagram of an entropy-decoding unit according to anexemplary embodiment of the present invention; and

FIG. 11 is a flowchart illustrating a method of entropy-decoding videodata according to an exemplary embodiment of the present invention.

DETAILED DESCRIPTION OF THE INVENTION

Hereinafter, exemplary embodiments of the present invention will bedescribed in detail with reference to the accompanying drawings.

FIG. 3 is a block diagram of a video encoder 300 according to anexemplary embodiment of the present invention.

Referring to FIG. 3, the video encoder 300 includes a residue generationunit 310, a transformation unit 320, a quantization unit 330, and anentropy-coding unit 340.

The residue generation unit 310 generates a residual block of thecurrent block. More specifically, the residue generation unit 310generates a prediction block that is a prediction value for the currentblock by performing interprediction or intraprediction and subtracts theprediction block from the current block, thereby generating the residualblock.

The transformation unit 320 transforms the residual block generated bythe residue generation unit 310 into the frequency domain, therebygenerating coefficients of the frequency domain for the residual block.Preferably, but not necessarily, the transformation unit 320 performsdiscrete cosine transformation (DCT) on the residual block, therebygenerating DCT coefficients. In the following description, DCTcoefficients will be taken as an example of the coefficients of thefrequency domain for convenience of explanation. However, it can beeasily understood by those of ordinary skill in the art that the DCTcoefficients are only an example of the coefficients of the frequencydomain and all coefficients generated by transforming the residual blockto the frequency domain fall within the scope of the present invention.

The quantization unit 330 quantizes the DCT coefficients generated bythe transformation unit 320. More specifically, the quantization unit330 quantizes the generated DCT coefficients using a predeterminedquantization parameter (QP).

The entropy-coding unit 340 performs entropy-coding on the DCTcoefficients quantized by the quantization unit 330. More specifically,after the quantization unit 330 re-arranges the DCT coefficientsone-dimensionally by scanning the DCT coefficients, the entropy-codingunit 340 independently entropy-codes runs and levels using run-levelcoding. In particular, the entropy-coding unit 340 according to anexemplary embodiment of the present invention binarizes coefficientshaving values other than ‘0’ from among the coefficients of thefrequency domain, i.e., levels, using different binarization methods andperforms binary arithmetic coding on the binarized coefficients, as willnow be described in detail with reference to FIG. 4.

FIG. 4 is a block diagram of the entropy-coding unit 340 according to anexemplary embodiment of the present invention.

Referring to FIG. 4, the entropy-coding unit 340 includes a binarizationunit 410 and an arithmetic coding unit 420.

The binarization unit 410 receives the quantized DCT coefficients fromthe quantization unit 330 and binarizes some of the received DCTcoefficients, which have values other than ‘0’, by using differentbinarization methods.

Preferably, but not necessarily, the binarization unit 410 according toan exemplary embodiment of the present invention includes a groupingunit 412 and a binarization performing unit 414.

The grouping unit 412 divides the DCT coefficients received from thequantization unit 330 into a plurality of groups according to whetherfrequencies of the DCT coefficients are high or low, as will now bedescribed in detail with reference to FIG. 5.

FIG. 5 illustrates grouping of the DCT coefficients according to anexemplary embodiment of the present invention. FIG. 5 illustrates a casewhere DCT is performed on a 4×4 block.

In a transformation coefficient block quantized by the quantization unit330 as illustrated in FIG. 5, coefficients in an upper left portion ofthe transformation coefficient block are low-frequency cosinecoefficients and coefficients in a lower right portion of thetransformation coefficient block are high-frequency cosine coefficients.As discussed above in relation to the related art, levels are mostlylocated in the upper left portion of the transformation coefficientblock. The levels in the upper left portion of the transformationcoefficient block are likely to have greater values than those of levelslocated in the lower right portion of the transformation coefficientblock.

Thus, the binarization unit 340 according to an exemplary embodiment ofthe present invention groups the DCT coefficients into a plurality ofgroups according to whether frequencies of the DCT coefficients are highor low in order to binarize the groups using different binarizationmethods. As illustrated in FIG. 5, the DCT coefficients may be groupedinto groups A, B, C, and D. However, it can be easily understood bythose of ordinary skill in the art that the method of grouping the DCTcoefficients illustrated in FIG. 5 is only an example and the DCTcoefficients can also be grouped using methods other than thatillustrated in FIG. 5.

Referring back to FIG. 4, once the grouping unit 412 groups the DCTcoefficients into a plurality of groups, the binarization performingunit 414 performs binarization on the plurality of groups usingdifferent binarization methods, as will now be described in detail withreference to FIG. 6.

FIG. 6 is a table illustrating binarization of DCT coefficientsaccording to an exemplary embodiment of the present invention.

Referring to FIG. 6, among DCT coefficients included in the group Aillustrated in FIG. 5, levels are binarized using a combination oftruncated unary binarization having a maximum code value (cMax) of ‘7’and second order exponential Golomb binarization.

More specifically, levels having absolute values (abs_level), whichhereinafter will be briefly referred to as values, of ‘1’-‘7’ arebinarized using truncated unary binarization and levels having valuesgreater than ‘7’ are binarized using a combination of truncated unarybinarization and exponential Golomb binarization.

Among DCT coefficients included in the group B, levels are binarizedusing a combination of truncated unary binarization having a maximumcode value of ‘8’ and first order exponential Golomb binarization.

More specifically, levels having values of ‘1’-‘8’ are binarized usingtruncated unary binarization and levels having values greater than ‘8’are binarized using a combination of truncated unary binarization andexponential Golomb binarization.

Among DCT coefficients included in the group C, levels are binarizedusing a combination of truncated unary binarization having a maximumcode value of ‘10’ and first order exponential Golomb binarization.

More specifically, levels having values of ‘1’-‘10’ are binarized usingtruncated unary binarization and levels having values greater than ‘10’are binarized using a combination of truncated unary binarization andexponential Golomb binarization.

Among DCT coefficients included in the group D (not show in FIG. 6),levels are binarized using a combination of truncated unary binarizationhaving a maximum code value of ‘14’ and 0^(th) order exponential Golombbinarization.

More specifically, levels having values of ‘1’-‘14’ are binarized usingtruncated unary binarization and levels having values greater than ‘14’are binarized using a combination of truncated unary binarization andexponential Golomb binarization.

When the DCT coefficients are binarized using different binarizationmethods as illustrated in FIG. 6, large values of the levels of thegroup A can be expressed by a small number of bin strings and smallvalues of the levels of the group D can be expressed by a small numberof bin strings.

For example, a level has a value of ‘19’. When an absolute value of aDCT coefficient belonging to the group A is ‘19’, it is expressed by atotal of 19 bin strings according to the related art illustrated in FIG.2. However, according to the present invention, the absolute value isexpressed by 13 bin strings. In other words, DCT coefficients of thegroup A, which are likely to have greater level values than those of DCTcoefficients of the other groups, can be expressed by a small number ofbin strings.

A binarization method may be changed by simultaneously changing amaximum code value of unary binarization and an order of exponentialGolomb coding as illustrated in FIG. 6, but it may also be changed bychanging only one of the maximum code value of unary binarization andthe order of exponential Golomb coding.

FIG. 7 is a table illustrating binarization of DCT coefficientsaccording to another exemplary embodiment of the present invention.

The level values and probability distribution of the DCT coefficientscan also be changed according to quantization parameters (QPs). It hasbeen experimentally proven that the probability distribution of thelevel values of the group A illustrated in FIG. 5 is changed with theQPs. Thus, it is necessary to change a method of binarizing the DCTcoefficients based on the QPs.

Referring to FIG. 7, methods of binarizing the DCT coefficients includedin the groups A, B, and C illustrated in FIG. 5 vary according to theQPs. ‘T’ indicates the maximum code value of unary binarization and ‘k’indicates the order of exponential Golomb coding.

Among the DCT coefficients included in the group D (not shown in FIG.7), levels are binarized using a combination of truncated unarybinarization having a maximum code value of ‘14’ and 0^(th) orderexponential Golomb binarization like in the prior art.

Referring back to FIG. 4, the DCT coefficients binarized by thebinarization performing unit 414 are delivered to the arithmetic codingunit 420. The arithmetic coding unit 420 performs context-adaptivevariable length coding (CAVLC) on the binarized DCT coefficients,thereby completing entropy-coding.

FIG. 8 is a flowchart illustrating a method of entropy-coding video dataaccording to an exemplary embodiment of the present invention.

Referring to FIG. 8, the entropy-coding unit 340 according to anexemplary embodiment of the present invention binarizes DCT coefficientsgenerated by performing DCT on a residual block of the current block,using different binarization methods, in operation 810. Theentropy-coding unit 340 may group the DCT coefficients into a pluralityof groups according to whether frequencies of the DCT coefficients arehigh or low and binarize the groups using different binarizationmethods. The DCT coefficients that are subject to binarization are DCTcoefficients that have been quantized using a predetermined QP afterhaving DCT performed thereon.

In operation 820, the entropy-coding unit 340 performs binary arithmeticcoding on the DCT coefficients binarized in operation 810. Preferably,but not necessarily, the entropy-coding unit 340 performs CABAC. Binstrings generated by the binary arithmetic coding are inserted into abitstream.

FIG. 9 is a block diagram of a video decoder 900 according to anexemplary embodiment of the present invention.

Referring to FIG. 9, the video decoder 900 includes an entropy-decodingunit 910, an inverse transformation unit 920, and a reconstruction unit930.

The entropy-decoding unit 910 receives a bitstream including dataregarding a residual block of the current block and entropy-decodes thedata regarding the residual block included in the received bitstream.

The data regarding the residual block includes DCT coefficients thathave been entropy-coded by a method of entropy-coding video dataaccording to an exemplary embodiment of the present invention. In otherwords, the data regarding the residual block includes data regarding DCTcoefficients that are entropy-coded by binarizing DCT coefficients,generated by performing DCT on the residual block, by using differentbinarization methods and then binary-arithmetically coding the binarizedDCT coefficients.

FIG. 10 is a block diagram of the entropy-decoding unit 910 according toan exemplary embodiment of the present invention.

Referring to FIG. 10, the entropy-decoding unit 910 includes anarithmetic decoding unit 1010 and an inverse binarization unit 1020.

The arithmetic decoding unit 1010 performs binary arithmetic decoding onthe data regarding the residual block included in the bitstream.Preferably, but not necessarily, the arithmetic decoding unit 1010performs CAVLC.

The binarized DCT coefficients are generated by binary arithmeticdecoding and then delivered to the inverse binarization unit 1020.

The inverse binarization unit 1020 performs inverse binarization on thebinarized DCT coefficients using different inverse binarization methods.The inverse binarization unit 1020 performs inverse binarization usinginverse binarization methods corresponding to binarization methodsdescribed with reference to FIGS. 6 and 7. More specifically, theinverse binarization unit 1020 performs inverse binarization usingdifferent inverse binarization methods by considering the frequencies ofthe DCT coefficients and QPs.

Preferably, but not necessarily, the inverse binarization unit 1020includes a grouping unit 1022 and an inverse binarization performingunit 1024.

The grouping unit 1022 groups the DCT coefficients that undergo binaryarithmetic decoding in the arithmetic decoding unit 1010 into aplurality of groups according to whether frequencies of the DCTcoefficients are high or low. As illustrated in FIG. 5, the DCTcoefficients may be grouped into 4 groups.

The inverse binarization performing unit 1024 performs inversebinarization on the plurality of groups using different inversebinarization methods. More specifically, the inverse binarizationperforming unit 1024 performs inverse binarization on the groups usingdifferent unary binarization/exponential Golomb binarization methods.For example, the inverse binarization performing unit 1024 performsinverse binarization on coefficients having level values other than ‘0’from among the binarized DCT coefficients, i.e., levels. Differentinverse binarization methods are applied to different groups to whichthe levels belong.

The inverse binarization performing unit 1024 uses differentbinarization methods by changing at least one of the maximum code valueof unary binarization and the order of exponential Golomb binarization.In other words, the inverse binarization performing unit 1024 performsinverse binarization by applying inverse binarization methodscorresponding to binarization methods applied in binarization of DCTcoefficients in a video encoder to the groups.

Referring back to FIG. 9, the DCT coefficients that are entropy-decodedby being inversely binarized by the inverse binarization unit 1020 areinversely quantized by the inverse quantization unit 930. The inversetransformation unit 920 performs inverse discrete cosine transformation(IDCT) on the DCT coefficients that are inversely quantized by theinverse quantization unit 930, thereby reconstructing the residualblock.

The reconstruction unit 940 generates a prediction block that is aprediction value for the current block by performing interprediction orintraprediction and adds the generated prediction block to the residualblock reconstructed by the inverse transformation unit 920, therebyreconstructing the current block.

FIG. 11 is a flowchart illustrating a method of entropy-decoding videodata according to an exemplary embodiment of the present invention.

Referring to FIG. 11, the entropy-decoding unit 910 performs binaryarithmetic decoding on data regarding a residual block in operation1110. Preferably, but not necessarily, the entropy-decoding unit 910performs CAVLC as mentioned above. Binarized DCT coefficients for theresidual block are generated as the binary arithmetic decoding result.

In operation 1120, the entropy-decoding unit 910 performs inversebinarization on the binarized DCT coefficients by using differentinverse binarization methods. In other words, the entropy-decoding unit910 performs inverse binarization on the binarized DCT coefficientsusing different inverse binarization methods.

More specifically, the entropy-decoding unit 910 may group the binarizedDCT coefficients into a plurality of groups according to whetherfrequencies of the DCT coefficients are high or low and perform inversebinarization by applying different inverse binarization methods to thegroups. Among the binarized DCT coefficients, coefficients having levelvalues other than ‘0’, i.e., levels, are inversely binarized.

The present invention can also be embodied as computer-readable code ona computer-readable recording medium or other computer readable medium.The computer-readable recording medium is any data storage device thatcan store data which can be thereafter read by a computer system.Examples of the computer-readable recording medium include read-onlymemory (ROM), random-access memory (RAM), CD-ROMs, magnetic tapes,floppy disks, and optical data storage devices An example of othercomputer readable media is carrier waves. The computer-readablerecording medium can also be distributed over network coupled computersystems so that the computer-readable code is stored and executed in adistributed fashion.

According to the present invention, in entropy coding, DCT coefficientsare adaptively binarized into variable length codes according to whetherfrequencies of the DCT coefficients are high or low and the binarizedDCT coefficients are binary-arithmetically coded, thereby improving thecompression efficiency of video data.

While the present invention has been particularly shown and describedwith reference to an exemplary embodiment thereof, it will be understoodby those of ordinary skill in the art that various changes in form anddetail may be made therein without departing from the spirit and scopeof the present invention as defined by the following claims.

What is claimed is:
 1. A method for entropy-decoding video data, themethod comprising: receiving a bitstream including a coefficientregarding a residual block; performing arithmetic decoding on thereceived bitstream to generate a binarized coefficient; and inverselybinarizing the binarized coefficient including a first bin stringrelated to a truncated inverse binarization method, using at least onefrom among the truncated inverse binarization method and an ExponentialGolomb inverse binarization method to reconstruct the coefficient,wherein: when the binarized coefficient further includes second binstring related to a maximum code value of the truncated inversebinarization method, the binarized coefficient is inversely binarizedusing the truncated inverse binarization method and the ExponentialGolomb inverse binarization method, the second bin string is related tothe Exponential Golomb inverse binarization method, and the maximum codevalue of the truncated inverse binarization method varies according to aposition of the coefficient in the residual block, when the binarizedcoefficient does not include the second bin string, theinversely-binarized coefficient is less than or equal to the maximumcode value of the truncated inverse binarization method, and when thebinarized coefficient includes the first bin string and the second binstring, the inversely-binarized coefficient is greater than the maximumcode value of the truncated inverse binarization method.
 2. The methodof claim 1, wherein a frequency component of the coefficient isdetermined according to the position of the coefficient, and wherein thebinarized coefficient is a discrete cosine transformation (DCT)coefficient generated by performing DCT on the residual block.
 3. Themethod of claim 2, wherein the inversely binarizing the binarizedcoefficient comprises inversely binarizing discrete cosinetransformation (DCT) coefficient based on the position of the DCTcoefficient.
 4. The method of claim 3, wherein the inversely binarizingthe binarized coefficient comprises inversely binarizing the DCTcoefficient using truncated inverse binarization method of differentmaximum code value from a maximum code value of another DCT coefficientin the residual block.